Mobile robotic devices are being used more and more frequently in a variety of industries for executing different tasks with minimal or no human interactions. Such devices rely on various sensors to navigate through their environment and avoid driving into obstacles.
Infrared sensors, sonar and laser range finders are some of the sensors used in mobile robotic devices. Infrared sensors typically have a low resolution and are very sensitive to sunlight. Infrared sensors that use a binary output can determine whether an object is within a certain range, but are unable to accurately determine the distance to the object. Sonar systems rely on ultrasonic waves instead of light. Under optimal conditions, sonar systems can be very accurate, however, sonar systems have limited coverage areas; if used in an array, they can produce cross-talk and false readings; if they are installed too close to the ground, signals can bounce off the ground, degrading accuracy; and sound-absorbing materials in the area can produce erroneous readings.
Laser Distance Sensors (LDS) are very accurate distance measurement methods that can be used on robotic devices, but, due to their complexity and cost, these sensors are typically not a suitable option for robotic devices intended for day-to-day home use. These systems generally use two types of measurement methods: Time-of-Flight (ToF) and Triangulation. In ToF methods, the distance of an object is calculated based on the round trip of the emission and reception of a signal. In Triangulation methods, there is a source and a sensor on the device with a fixed baseline. The emitting source emits the laser beam at a certain angle. When the sensor receives the beam, the sensor calculates the degree at which the beam entered the sensor. Using those variables, the distance traveled by the laser beam may be calculated with triangulation.
A need exists for an improved method for measuring distance that is not susceptible to the above-mentioned restrictions.